Most commercial large-scale production of proteins uses column chromatography and synthetic membranes to fractionate and concentrate proteins. Though the requisite multiple recovery steps increase purity, yields drop quickly and expenses rise. Improving the performance of these processes is therefore a high priority. Nature has already solved this kind of protein enrichment problem with the nuclear pore complex (NPC), the macromolecular machine that efficiently segregates proteins between the nucleus and cytoplasm of all eukaryotic cells. Since we now have an understanding of the mechanism by which the NPC transports proteins, our goal is to mimic the molecular machinery of the NPC, with its exquisite selectivity and high throughput, in a robust synthetic platform. Our approach is one of reverse engineering, in which we will dissect the nuclear transport system to elucidate its key elements in order to duplicate them. We will use the yeast NPC, the best understood system, as our starting point. Our approach is one of reverse engineering, in which we will dissect the nuclear transport system to elucidate its key elements in order to duplicate them. We will use the yeast NPC, the best understood system, as our starting point. Specific Aim 1 and Specific Aim 2 seek to detail how the NPC is configured to function as a transporter. For this, we must separate those components that are essential for transport from those needed for other NPC functions, such as self-assembly and NE maintenance, and learn how those components function. Following this, we will study in detail the behavior of the key components needed for nuclear transport, to understand why they make the NPC function so efficiently in vivo. In Specific Aim 3 we will develop a computational simulation of the NPC to explore how to translate these optimal parameters into an artificial machine, and in Specific Aim 4 we will explore several avenues to build such machines at various scales. [unreadable] [unreadable]